PhD Student: Léopold Beeker
Title: Associations Between Diet and Gut Microbiota in Relation to Host Overweight – An Epidemiological Approach Within the NutriNet-Santé Cohort
Supervisors: Dr. Mélanie Deschasaux-Tanguy, Dr. Mathilde Touvier
Doctoral School: ED Galilée
Promotion: 2024
Funding: University Sorbonne Paris Nord
Thesis Abstract:
In recent years, the gut microbiota has garnered growing attention from both the scientific community and the public as a key component of human health. Alterations in gut microbiota composition have been identified in various pathological conditions, particularly obesity. Diet plays a crucial role in shaping the gut microbiota. Over the past decades, significant changes in dietary patterns have occurred, marked by the rise of "Western" dietary profiles. These are nutritionally characterized by a reduction in dietary fiber and an increase in sugars, saturated fats, and animal-derived proteins, along with a substantial proportion of "ultra-processed" foods.
In humans, most studies investigating the relationship between diet and gut microbiota have been conducted on small sample sizes. More recently, large-scale studies have emerged (n=1,000 to 8,000), but these studies are often limited in the level of detail regarding dietary data. Similarly, food additives are suspected to contribute to the observed health effects of "ultra-processed" foods, based on concerning experimental findings linking various additives (e.g., emulsifiers, sweeteners) to gut microbiota alterations. However, no general population data are currently available.
The objective of this PhD work is therefore to study associations between diet and gut microbiota in the context of overweight and obesity. Specifically, the project will aim to:
1) Investigate associations between gut microbiota profiles and diet, focusing on detailed dietary fiber intake and exposure to food additives, particularly sweeteners, emulsifiers, and additive mixtures.
2) Explore associations between diet-related gut microbiota profiles and overweight conditions, examining: prevalence (cross-sectional) and incidence (prospective) of overweight and obesity, weight changes (prospective) ; interaction and mediation studies.
This research will utilize data from the NutriNet-Santé cohort, coordinated by EREN. Launched in 2009, this French web-based cohort includes over 177,000 participants. Advanced statistical methods tailored to gut microbiota analysis will be employed, including dimension reduction techniques (e.g., PCA, PCoA, PLS) and machine learning approaches (e.g., random forests).
